In waterflooding process, the time for breakthrough of injecting fluid into a production well is of great importance. Predicting this time helps in designing reservoir development plan. Due to uncertainties in reservoir characterization, estimating the breakthrough is not easy, so alternative methods to estimate quickly the breakthrough time is useful. The percolation method uses limited available reservoir data to predict the breakthrough time distribution, and it may be used for engineering applications. However, implementation of this to real reservoirs requires some adjustments. The aim of this study is to show how percolation approach can be used to real problems. In particular, the effects of permeability contrast between the reservoir and non-reservoir parts in the model are investigated. In order to use the breakthrough scaling function to more realistic reservoir models, a dimensionless breakthrough time was used. The analysis of the breakthrough time of models with zero permeability background (tk=0) and such time for the case of non-zero permeability background (tk=αk) shows a linear dependency which can be used to find breakthrough time distribution. Hence, this correction extends the applicability of the percolation method for predicting breakthrough time when permeability of the system background is not zero.

The miscible displacement process appears to be an increasingly feasible method for the extraction of oil from depleted reservoirs. How­ever, there is a lack of fundamental understanding of how fracture geometrical characteristics impact the oil recovery efficiency in this type of enhanced oil recovery technique. In this work, a series of experimental tests were conducted whereby the n-Heptane as a solvent displaced n-Decane in the glass micro-models having different fracture geometries. It has been observed that the breakthrough time is decreased with increasing the fractures’ length. In contrast, breakthrough time is increased when increasing the fractures orientation angle related to flow direction. A correlation has been presented for the breakthrough time as a function of fracture length and its orientation.

Background and Purpose: Rapid and accurate identification of molds is critical in clinical microbiology, particularly for immunocompromised patients at increased risk of fungal infections. Traditional methods, such as culture and microscopy, are time-consuming and may lack species-level specificity. The matrix-assisted laser desorption/ionization time-of-flight mass spectrometry matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) provides a promising alternative due to its speed and accuracy. This study aimed to standardize Vitek MS for mold identification and compare its effectiveness with traditional phenotypic methods, assessing its reliability, turnaround times, and cost-effectiveness in clinical settings. Materials and Methods: A retrospective examination of 248 anonymized mold isolates was conducted at Hinduja Hospital, with 182 isolates successfully revived. Both Vitek MS and phenotypic techniques were used to identify the molds, and the concordance rate between the two methods was calculated. Results: Vitek MS accurately identified 169 out of the 182 isolates, yielding a concordance rate of 92.85% with phenotypic methods. Of the remaining isolates, 1 was misidentified, 4 could not be identified, and 8 were not represented in the database. Conclusion: Vitek MS proved to be a highly accurate and time-efficient tool for mold identification, enhancing clinical diagnostics. Expansion of its database is crucial for broader mold identification. This study supported integration of Vitek MS into routine laboratory practice, aiding in timely antifungal treatment, improving patient outcomes, and assisting in outbreak detection and public health management

Water flooding is a well known secondary mechanism for improving oil recovery. Conventional approach to evaluate the performance of a water flooding process (e.g. breakthrough and post breakthrough behavior) is to establish a reliable geological reservoir model, upscale it, and then perform flow simulations. To evaluate the uncertainty in the breakthrough time or post breakthrough behavior, this procedure has to be repeated for many realizations of the geological model, which takes many hours of CPU time. Moreover, during the early stage of reservoir life, when data is scare, breakthrough and post breakthrough time behavior prediction are usually based on analogues or rules of thumb. Alternative statistical approach is to use percolation theory to predict breakthrough and post breakthrough bahavior. The main contribution is to evaluate the applicability of the existing scaling laws of the breakthrough time by the numerical flow simulation results using the Burgan formation dataset of Norouz offshore oilfield in the south of Iran. Moreover, we extend the scaling to the post breakthrough behavior. There is good agreement between the predictions from the percolation based expressions and the numerical simulation results. Moreover, the prediction from the scaling law took a fraction of a second of CPU times (as it only needs some algebraic calculations) compared with many hours required for the conventional numerical simulations.

Sepsis remains a critical challenge in clinical practice, leading to high morbidity and mortality rates. Current treatments focus on infection control and supportive care but often fail to address the complex pathophysiology of sepsis (1, 2). Emerging research suggests that estrogen, particularly estradiol (E2), could offer novel therapeutic benefits due to its antiinflammatory, renoprotective, and immune-modulating properties (3).